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Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/RUSLE
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Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment. Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures. Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software. Subsequently, the different classes of soil erosion and percentage area under these classes were identified. The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.80 t.ha-1.yr-1 and 6.64 t.ha-1.yr-1, respectively. The areas under severe risk were 1.09 % and 1.80 %, and very severe risk areas were 1.57 % and 1.83 % as estimated by USLE and RUSLE model, respectively. As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state.
Indian Society of Agricultural Engineers
Title: Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/RUSLE
Description:
Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment.
Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures.
Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software.
Subsequently, the different classes of soil erosion and percentage area under these classes were identified.
The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.
80 t.
ha-1.
yr-1 and 6.
64 t.
ha-1.
yr-1, respectively.
The areas under severe risk were 1.
09 % and 1.
80 %, and very severe risk areas were 1.
57 % and 1.
83 % as estimated by USLE and RUSLE model, respectively.
As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state.
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